Octopus Basics

Mobile robotics à la carte.

Octopus Basics is a versatile robot for a variety of uses, from heavy load transport to monitoring. It adapts according to your needs.

AUTONOMY

The size of the chassis and its weight allow us to ship a large volume of batteries allowing a range of monitoring mode of more than 20 hours. Also, we use a non-contact induction charging system.
Battery characteristics: 100 A / hour; 14 kg.

EQUIPMENT

The chassis of our robots include all the engine, batteries and all the management electronics of the whole. They are equipped with 4 high power brushless motors allowing onboard loads up to 100 kg. They also have 4 driving wheels guaranteeing a use on all terrains. What's more, the waterproof structure allows amphibious use (land and water).

AUTONOMOUS GUIDANCE

We use a cascade of sensors in order to realize the mapping and the trajectory of the robot: LIDAR laser extended range to +/- 100 meters, 3 depth cameras (40 cm to approximately 6 meters), ultrasonic system (0 to 2.5 meters ), thermal imaging cameras and microwave radar (in progress).

- AI IN ALL ITS SPLENDOR -(ARTIFICIAL INTELLIGENCE)

Each technology is known and mastered in the context of simple applications in the laboratory environment.
In our case, the environment is closer to the difficulty of an autonomous vehicle than a laboratory robot. We must take into account many environmental disturbance parameters (non-stable, non-flat terrain, presence of animals, dust, fog, etc.).
In order to reach the desired result we put a complex multi-sensor methodology. By definition, we consider the result of each sensor as potentially wrong and therefore challenged by the result of others. All the results of the sensor measurements are independent of each other and possibly corrected if necessary.

For example, the measurement of LIDAR is directly correlated with the result of the base of the IMU. The audometry of the wheel sensors is correlated with the accelerometer of the IMU (skating case on slippery ground). The position received from the depth cameras with respect to a local coordinate system, such as a wall, a border or a feeder line, enables the LIDAR data to be readjusted with greater precision. Cameras and ultrasound identify temporary or permanent obstacles in order to make an avoidance trajectory and update the map.